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2024 06 v.56 32-38
基于多尺度特征融合和注意力机制的水面死鱼检测方法
基金项目(Foundation): 国家自然科学基金项目(62002180);; 河南省科技攻关项目(202102210362,232102210149);; 河南省高等学校重点科研项目(24A520030);; 南阳师范学院实验室开放项目(SYKF2021029)
邮箱(Email): lihe@nynu.edu.cn;
DOI: 10.13705/j.issn.1671-6841.2023149
中文作者单位:

南阳师范学院计算机科学与技术学院;河南中光学集团有限公司;河南科技大学信息工程学院;

摘要(Abstract):

死鱼对于水域生态和饮水安全存在巨大威胁,由于水面环境复杂,导致现有目标检测算法在死鱼检测任务中存在漏检、误检等情况。为此,以单次多边框检测(single shot multibox detector, SSD)为基础提出一种基于多尺度特征融合和注意力机制的水面死鱼检测方法FFA-SSD(SSD with feature fusion and attention)。首先,采用计算量和参数量更少且特征提取能力更强的残差网络ResNet50替换VGG16主干网络;其次,设计了多尺度特征融合模块,增强浅层特征和高层语义信息的融合;然后,引入通道注意力机制,抑制特征融合带来的冗余信息干扰,提升网络对目标的关注度;最后,设计了一种适用于小目标检测的数据增强算法,扩充训练数据中的小目标数量,丰富训练背景。实验结果表明,同现有目标检测算法相比,FFA-SSD算法可以更好地识别水面死鱼,检测精度达到93.5%。

关键词(KeyWords): SSD;;目标检测;;特征融合;;注意力机制;;数据增强
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基本信息:

DOI:10.13705/j.issn.1671-6841.2023149

中图分类号:TP18;TP391.41;X832

引用信息:

[1]杨帅鹏,李贺,刘金江等.基于多尺度特征融合和注意力机制的水面死鱼检测方法[J].郑州大学学报(理学版),2024,56(06):32-38.DOI:10.13705/j.issn.1671-6841.2023149.

基金信息:

国家自然科学基金项目(62002180);; 河南省科技攻关项目(202102210362,232102210149);; 河南省高等学校重点科研项目(24A520030);; 南阳师范学院实验室开放项目(SYKF2021029)

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